audit_seo_metadataUse this for a focused SEO/accessibility-signal check of supplied HTML. It does not fetch a live webpage; use audit_public_webpage for a URL.
| Name | Required | Description | Default |
|---|---|---|---|
| html | Yes | Raw HTML markup supplied by the user; this is not a webpage URL. |
| Name | Required | Description | Default |
|---|---|---|---|
| error | No | ||
| issues | Yes | ||
| overview | Yes | ||
| truncated | Yes | ||
| total_issues | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate a safe, read-only, idempotent operation, so the safety profile is covered. The description adds key behavioral context by explicitly stating it does not fetch a live webpage, clarifying the offline nature of the operation. This goes beyond annotations but isn't exhaustive; still, it effectively sets expectations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first states the purpose, the second clarifies a critical exclusion and provides an alternative. It is front-loaded, concise, and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With one parameter, a descriptive schema, comprehensive annotations, and an output schema, the description fully equips an agent to select and invoke the tool correctly. It explains the input type, the scope, and the alternative, making it complete for this tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with the 'html' parameter described as 'Raw HTML markup supplied by the user; this is not a webpage URL.' The description reinforces this by saying 'supplied HTML' and 'does not fetch a live webpage,' but it adds no new information beyond the schema. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs 'a focused SEO/accessibility-signal check of supplied HTML' with a specific verb ('audit') and resource ('SEO metadata'). It explicitly distinguishes itself from sibling 'audit_public_webpage' by noting this tool does not fetch live webpages, providing clear differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage guidance is explicit: use this when you have raw HTML to check, and use 'audit_public_webpage' when you have a URL. This directly addresses when to use vs. alternatives, leaving no ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: site audit, single page audit, SEO metadata check, broken links check, combined report generation, and separate validators for CSS, HTML, and JSON-LD. Descriptions explicitly clarify boundaries (e.g., 'does not fetch a live webpage' vs 'use for a live URL').
Tools use four different verb prefixes ('audit_', 'check_', 'generate_', 'validate_') without a unifying pattern, making the naming scheme somewhat inconsistent. While each prefix is reasonable, the lack of a consistent verb_noun structure reduces predictability.
With 8 tools, the set is well-scoped for a web validation server, covering the major validation tasks (HTML, CSS, JSON-LD, broken links, SEO signals, site audit) without unnecessary bloat. Each tool earns its place.
The tool surface covers core validation needs for public websites, but lacks some advanced SEO checks (e.g., mobile-friendliness, performance) and does not validate Schema.org vocabulary semantics. Minor gaps exist but do not severely hinder the server's primary purpose.